QuestionQ229
Data Ingestion and TransformationA company processes a CSV file containing millions of transaction records each day. The file resides in Amazon S3. Every transaction must be validated before a database update. The company requires a solution that processes the data in parallel. The solution must provide error handling that stops the entire process if more than 15% of records fail validation.
Which solution meets these requirements with the LEAST operational overhead?
- A Create an AWS Batch job that processes chunks of the file in parallel with a custom error tracking mechanism.
- B Use AWS Step Functions Distributed Map state with the ToleratedFailurePercentage field set to 15%.
- C Deploy an Amazon EMR cluster with Spark to process the file Configure a custom failure threshold to 15%.
- D Use AWS Lambda with S3 Batch Operations to process the file and track validation failures to be less than 15%.
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